Affiliation:
1. Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
2. Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
Abstract
Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that predictions from maximization of ribosome usage in a parsimonious flux model constrained by proteome allocation agree with the conserved ratios of translation factors. The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion constants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry.
Funder
National Institutes of Health
National Science Foundation
Richard and Susan Smith Family Foundation
Pew Charitable Trusts
Alfred P. Sloan Foundation
Kinship Foundation
National Research Council Canada
Howard Hughes Medical Institute
Publisher
eLife Sciences Publications, Ltd
Subject
General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience
Cited by
4 articles.
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